Fractal models described the universe as a chaotic system. Biology also can be explained by using these models in some extend. However I was wondering if some among us have experience in implementing fractal models. I would be extremely interested in looking at the miRNA regulatory networks on the basis of fractal behavior. Thanks.
I think that fractal model to model microRNA regulatory network is a great idea, but we must be sure that we are modeling a real situation. Self-similarity involve a hierarchical organization of the topology, but we are not sure that microRNA regulatory network is a hierarchical network or not. In my opinion it is a network with a high level of degeneracy. In addition, we really don't know the growing rules, the generative function, neither the scale. Other relevant point is the real pattern of interactions, the competition among microRNAs involve a continuos remodeling of the network and I think that a model that optimize the robustness and degeneracy of the network are the most accurate for a microRNA network.
I am really interested and spectating to know other opinions.
This is a very interesting question and I am also interested if this may have a meaning.
I am also interested to learn about fractals. there was an paper in science about the fractal organization of higher order chromatin (leiberman et al 2009). and it would be interesting to explore this idea in miRNA reg. networks too. a paper on similar topic is (The Fuzzy Logic of MicroRNA Regulation: A Key to Control Cell
Complexity
Andrea Ripoli*,1, Giuseppe Rainaldi2,3, Milena Rizzo2, Alberto Mercatanti2 and Letizia Pitto2).
Some years ago I was amazed with fractals. They represent a part of a whole but conserving the same configuration of this whole. It would be very interesting if someone could demonstrate the occurrence of fractals in the control of gene expression, involving or not, microRNAs or other controlling elements. But this make sense ? Or we are just speculating …
Use of fractal models will be useful; however, it will approach to the single base pair resolution, below that, one probably can't go for DNA/RNA neuclic acids mediated activity to explain gene function and expression control.
Hope this helps you.
I think that fractal model to model microRNA regulatory network is a great idea, but we must be sure that we are modeling a real situation. Self-similarity involve a hierarchical organization of the topology, but we are not sure that microRNA regulatory network is a hierarchical network or not. In my opinion it is a network with a high level of degeneracy. In addition, we really don't know the growing rules, the generative function, neither the scale. Other relevant point is the real pattern of interactions, the competition among microRNAs involve a continuos remodeling of the network and I think that a model that optimize the robustness and degeneracy of the network are the most accurate for a microRNA network.
I am really interested and spectating to know other opinions.
Hi all... thanks for the valuable comments. I would like just to point your attention to the recently published paper in NAR about fractal models of chromatin organization.
http://nar.oxfordjournals.org/content/early/2012/07/23/nar.gks586.full
Waiting for your criticisms and suggestions.
We did not work with fractal models for miRNAs , but we have some experience with fractality of chromatin in different cancer models ( some free links below).Please note that a fractal organization can be found at different levels in the nucleus ( DNA sequences, chromatin folding, staining pattern and so on) So, why not looking for fractal models for miRNAs.? An excellent idea !
links to free articles :
http://www.ncbi.nlm.nih.gov/pubmed/22122044
http://www.ncbi.nlm.nih.gov/pubmed/21698234
http://www.ncbi.nlm.nih.gov/pubmed/20525386
for the following ( unfortunately not free article) you may send a e-mail to
http://www.ncbi.nlm.nih.gov/pubmed/16675881
kind regards
K.Metze
This Springer Textbook chapter is on ResearchGate. Provides a review of tensor- and fractal-geometrical unification of genomics and neuroscience. Self-similarity of miRNAs is quite visible, while the dual (measurement- and production-type) valences, while mathematically distinct, and so is their origin from ncDNA and cDNA, respectively, does call for a bit of deeper study. https://www.researchgate.net/publication/228096409_RECURSIVE_GENOME_FUNCTION_OF_THE_CEREBELLUM_GEOMETRIC_UNIFICATION_OF_NEUROSCIENCE_AND_GENOMICS_Andras_J._Pellionisz1_Roy_Graham2_Peter_A._Pellionisz3_Jean-Claude_Perez4in_Handbook_of_the_Cerebellum_and_Cerebellar_DisordersManto_M._Gruol_D._Schmahmann_J._Koibuchi_N._Rossi_F._(Eds.)ISBN_978-94-007-1333-8Due_September_24_2012httpwww.springer.combiomedneurosciencebook978-94-007-1332-1more_web_references_httpsplus.google.com103572438711329205534postsDPw4yr5peTvhttpgold The chapter is also available (free pdf) here http://www.junkdna.com/pellionisz_unification/
Chapter Recursive Genome Function of the Cerebellum: Geometric Unifi...
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